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Improved detector response characterization method in ISOCS and LabSOCS

  • R. Venkataraman
  • F. Bronson
  • V. Atrashkevich
  • M. Field
  • B. M. Young
Article

Summary

The In-Situ Object Calibration Software (ISOCS) and the Laboratory Sourceless Calibration Software (LabSOCS) developed and patented by Canberra Industries have found widespread use in the gamma-spectrometry community. Using the ISOCS methodology, one can determine the full energy peak efficiencies of a germanium detector in the 45 keV-7 MeV energy range, for practically any source matrix and geometry. The underlying mathematical techniques used in ISOCS (and LabSOCS) have undergone significant improvements and enhancements since their first release in 1996. One of these improvements is  a spatial response characterization technique that is capable of handling the large variations in efficiency that occurs within a small region. The technique has been in use in ISOCS and LabSOCS releases since 1999, and has significantly improved the overall quality of the close-in and off-axis response characterization for HPGe detectors, especially for Canberra’s Broad Energy Germanium (BEGe) detectors. In this method, the detector response is characterized by creating a set of fine spatial efficiency grids at 15 energies in the 45 keV-7 MeV range. The spatial grids are created in (r,⊝) space about the detector, with the radius r varying from 0 to 500 meters, and the angle ⊝ varying from 0 to π. The reference efficiencies for creating the spatial grids are determined from MCNP calculations using a validated detector model. Once the efficiency grids are created, the detector response can be determined at any arbitrary point within a sphere of 500-meter radius, and at any arbitrary energy within the specified range. Results are presented highlighting the improved performance achieved using the gridding methodology.

Keywords

Detector Response Gridding Spatial Grid Object Calibration Full Energy Peak 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag/Akadémiai Kiadó 2005

Authors and Affiliations

  • R. Venkataraman
    • 1
  • F. Bronson
    • 2
  • V. Atrashkevich
    • 3
  • M. Field
    • 4
  • B. M. Young
    • 5
  1. 1.Canberra Industries
  2. 2.Canberra Industries
  3. 3.Canberra Industries
  4. 4.Canberra Industries
  5. 5.Canberra Industries

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